Dynamic Simulation of Natural Gas Transmission Pipeline Systems through Autoregressive Neural Networks
نویسندگان
چکیده
Transmission of natural gas from its sources to end users in various geographical locations is carried out mostly by transmission pipeline networks (NGTNs). Effective design and operation NGTNs requires insights into their steady-state and, particularly, dynamic behavior. This, turn, calls for efficient computer-aided approaches furnished with accurate mathematical models. The conventional methods the simulation are computationally intensive. In this paper, use autoregressive neural cost-effective proposed. Considering length, diameter, roughness, elevation as main characteristics a single pipeline, network (NNPL) designed trained based on data process simulator. Arbitrary can then be easily constructed connecting developed NNPLs building blocks. performance NNPL demonstrated through number benchmark systems, where very good agreement results found.
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ژورنال
عنوان ژورنال: Industrial & Engineering Chemistry Research
سال: 2021
ISSN: ['0888-5885', '1520-5045']
DOI: https://doi.org/10.1021/acs.iecr.1c00802